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Applied Neuropsychology: Child Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/hapc20
Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population a
Brian Kavanaugh & Karen Holler
b
a
Department of Clinical Psychology , Antioch University New England , Keene , New Hampshire b
Department of Psychiatry and Human Behavior , Alpert Medical School of Brown University , Providence , Rhode Island Published online: 20 Nov 2012.
Click for updates To cite this article: Brian Kavanaugh & Karen Holler (2014) Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population, Applied Neuropsychology: Child, 3:2, 126-134, DOI: 10.1080/21622965.2012.731662 To link to this article: http://dx.doi.org/10.1080/21622965.2012.731662
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APPLIED NEUROPSYCHOLOGY: CHILD, 3: 126–134, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 2162-2965 print/2162-2973 online DOI: 10.1080/21622965.2012.731662
Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population Brian Kavanaugh Department of Clinical Psychology, Antioch University New England, Keene, New Hampshire
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Karen Holler Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island
Although the relationship between executive dysfunction and depressive disorders has been well established in the adult population, research within the adolescent population has produced mixed results. The present study examined executive-functioning subdomains in varying levels of self-reported depression within an adolescent inpatient sample diagnosed with primary mood disorders. Via retrospective chart review, the sample consisted of those adolescents (ages 13–18 years) who completed a combined psychological/neuropsychological assessment during hospitalization (N = 105). When the sample was divided into adolescents with mood disorders with self-reported depressive symptoms and adolescents with mood disorders without self-reported depressive symptoms, no differences in various executive functions were identified. There were also no correlations between overall self-reported depressive symptoms and overall executive functioning. However, there were negative correlations between select executive subdomains (e.g., problem solving and response inhibition) and certain depressive symptom subdomains (e.g., negative mood and interpersonal problems). Based on these findings, there was no difference in executive functions between mood disorders with depressive symptoms and mood disorders without depressive symptoms, although there may be select executive subdomains that are particularly involved in certain depressive symptoms, providing important information for the treatment of adolescent depression.
Key words:
adolescents, depression, executive functioning, inpatient, mood disorder
Recent research has identified neural correlates of depression, notably in the medial prefrontal cortex (Koenigs & Grafman, 2009; Murray, Wise, & Drevets, 2011; Price & Drevets, 2012), dorsolateral prefrontal cortex (DLPFC; Koenigs & Grafman; Ottowitz, Dougherty, & Savage, 2002), striatum (Ottowitz et al.; Price & Drevets), thalamus (Ottowitz et al.; Price & Drevets), and basal forebrain structures (Price & Drevets). Specific depressive symptoms have been identified within this neural Address correspondence to Brian Kavanaugh, Department of Clinical Psychology, Antioch University New England, 40 Avon Street, Keene, NH 03431. E-mail: [email protected]
network, including anhedonia, negative affect, and negative self-image/self-rumination (Koenigs & Grafman; Price & Drevets). The cognitive domain “executive functioning” consists of a heterogeneous set of cognitive functions responsible for planning, organizing and executing behaviors, problem solving, inhibiting inappropriate behavior and resisting distraction, fluency, working memory, and cognitive flexibility/set shifting, with impaired executive functions resulting in, or contributing to, a range of potential behavioral deficiencies (Anderson, 2002; Baron, 2004; Henry & Bettenay, 2010; Lezak, Howieson, & Loring, 2004; Mahone & Slomine, 2007; Willcutt, 2010).
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The prefrontal cortex (PFC) has typically been identified as the primary neural correlate of executive functioning, specifically in the subdomains of interference control/inhibition, working memory, planning, and set shifting (Collette et al., 2005; Willcutt, 2010). Notable structures associated with executive functioning include the circuit involving the DLPFC/ventrolateral PFC/orbitofrontal cortex (Collette et al.; Koenigs & Grafman, 2009; Ottowitz et al., 2002; Willcutt), thalamus (Ottowitz et al.; Willcutt), striatum (Ottowitz et al.) and basal ganglia (Willcutt). In addition to the association with prefrontal cortical regions, specific executive-functioning subdomains have been associated with differing neural substrates (Collette et al.). For example, selective attention and interference control have involved the right intraparietal sulcus, while set shifting/integration has been associated with the superior parietal region of the brain (Collette et al.). Based on the shared neural correlates between depression and executive functions (e.g., DLPFC, thalamus, striatum, and basal structures), theory has proposed and research has identified a link between adult depression and executive functioning, notably identifying executive dysfunction within adult depression (Castaneda, Tuulio-Henriksson, Marttunen, Suvisaari, & Lonnqvist, 2008; McDermott & Ebmeier, 2009; Ottowitz et al., 2002; Porter, Bourke, & Gallagher, 2007). However, the research on executive dysfunction within child and adolescent depression is still very inconsistent. With increased research in recent years within child and/or adolescent depression, the majority of research has identified at least partial executive dysfunction, specifically in interference control/response inhibition (Brooks, Iverson, Sherman, & Roberge, 2010; Cataldo, Noblie, Lorusso, Battaglia, & Molteni, 2005; Kyte, Goodyer, Sahakian, 2005), initiation/planning of behavior (Cataldo et al.; Maalouf et al., 2011), set shifting (Brooks et al.), working memory (Klimkeit, Tonge, Bradshaw, Melvin, & Gould, 2011; Matthews, Coghill, & Rhodes, 2008), verbal fluency (Klimkeit et al.), and impulsivity (Brooks et al.; Kyte et al.; Maalouf et al.). Alternatively, a portion of the research has found intact executive functioning (Favre et al., 2009; Halari et al., 2009; Hill, Ploetz, O’Jile, Bodzy, & Holler, in press; McClure, Rogeness, & Thompson, 1997). Two of these studies have examined the child/ adolescent depression–executive dysfunction association with self-report measures (Cataldo et al., 2005; Hill et al., in press). Cataldo et al. examined the executive functioning of 21 children and adolescents diagnosed with a mood disorder and 21 children and adolescents serving as a control group. Within those participants diagnosed with a mood disorder, there was a negative correlation between self-reported depressive symptoms and interference control/ response inhibition. Alternatively, Hill et al. examined the
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association between self-reported depressive symptoms and executive functioning in a mixed sample of 170 children and adolescents within an inpatient and outpatient setting. Results of this study indicated no significant association between self-reported depressive symptoms and any measured executive-functioning subdomains. Although findings within child and/or adolescent samples are important to consider, child and adolescent depression can have very significant differences, making it important to study these conditions as separate entities (Crowe, Ward, Dunnachie, & Roberts, 2006; Mash & Barkley, 2007; National Institute of Mental Health, 2001). Relatedly, some of the neuropsychological research has looked solely at adolescent depression and executive functioning (Halari et al., 2009; Klimkeit et al., 2011; Kyte et al., 2005; Maalouf et al., 2011; Matthews et al., 2008; McClure et al., 1997), with four studies finding at least partial evidence of dysfunction in select executive-functioning subdomains within adolescent depression (Klimkeit et al.; Kyte et al.; Maalouf et al.; Matthews et al.). Notably, two studies have examined the severity of adolescent depression in relation to executive functioning (Klimkeit et al., 2011; Maalouf et al., 2011). Maalouf et al. examined 40 adolescents diagnosed with major depressive disorder and dichotomized the sample into an active depression group and a remitted depression group based on a measure of self-reported depressive symptoms. Active depression was associated with impaired planning/problem solving and impulsivity when compared with the remitted depression group as well as a control group. These results indicated that when dichotomized, self-reported depressive symptoms might be associated with certain executive functions within adolescent depression. Klimkeit et al. examined the neuropsychological functioning of major and minor depression within a sample of 34 depressed adolescents and 33 adolescent controls. Although the authors noted executive dysfunction was not identified in either depressive group, both depression groups were characterized by impaired performance on tasks of working memory and verbal fluency. The present study attempted to contribute to the growing body of research on adolescent depression and executive functioning, specifically regarding the inconsistent findings regarding the association between self-reported depressive symptoms and executive functioning (Cataldo et al., 2005; Hill et al., in press; Maalouf et al., 2011). To do so, this study examined the association between selfreported depressive symptoms and executive functioning within an adolescent inpatient sample diagnosed with a mood disorder. Consistent with previous research, this study used a diagnosis of a mood disorder as inclusion criteria but used self-reported depressive symptoms to identify the association between executive functioning and depression (Cataldo et al.; Maalouf et al.).
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It was deemed that the term “executive functioning” was too heterogeneous in nature and therefore should not be defined as a unitary construct (Anderson, 2002; Baron, 2004, 2010; Henry & Bettenay, 2010; Willcutt, 2010). After reviewing the child and adolescent neuropsychological literature on executive functioning (Anderson; Baron, 2004, 2010; Henry & Bettenay; Willcutt), five subdomains of executive functioning were identified for the present study: (1) planning/problem solving; (2) set shifting/cognitive flexibility; (3) response inhibition/interference control; (4) fluency; and (5) working memory/simple attention. It was hypothesized that adolescent mood disorders with depressive symptoms would be associated with lower performance in a range of executive-functioning domains (e.g., planning/problem solving, inhibition/interference control, set shifting/cognitive flexibility, verbal fluency, and working memory/simple attention) compared with adolescent mood disorders without depressive symptoms. Based on the literature identifying shared neural correlates between depression and executive functioning, it was hypothesized that select depressive symptoms (e.g., negative affect, anhedonia, and negative self-image) would be negatively correlated with certain executive functions (e.g., inhibition/interference control, planning/problem solving, working memory/simple attention, and set shifting/cognitive flexibility), such that the increased presence of these depressive symptoms would be associated with decreased performance in these executive-functioning subdomains.
METHODS Participants and Procedure This study followed the ethical principles of the American Psychological Association. In addition, this study received institutional review board approval from Butler Hospital. This study is part of a research project examining neuropsychological correlates of psychiatric conditions in
adolescents at Butler Hospital, an inpatient psychiatric hospital. The data were gathered by retrospective chart review for inpatient adolescents who participated in a combined psychological/neuropsychological assessment during 2002 to 2012. Assessments were conducted by a clinical child neuropsychologist, a professional psychometrist, or a doctoral student in clinical psychology under the direct supervision of a child neuropsychologist. All hospitalized adolescents received an admitting diagnosis and a discharge diagnosis by their attending psychiatrist (or medical resident under supervision of an attending psychiatrist), based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental DisordersFourth Edition, Text Revision (American Psychiatric Association, 2000). However, not all adolescents participate in a psychological/neuropsychological assessment. Referrals for evaluation are based on the parent/guardian concerns or a request for additional information by the attending psychiatrist. Assessments are typically completed within a few days of the hospital admission. The present study focused on the relationship between self-reported depressive symptoms and performance on measures of executive functioning in mood disorders within the adolescent inpatient setting. Inpatients with a diagnosis of bipolar disorder, a pervasive developmental disorder (e.g., autistic disorder, Asperger’s disorder, Rett’s disorder, childhood disintegrative disorder, and pervasive developmental disorder-not otherwise specified [NOS]), or a psychotic disorder were not included in the study. Therefore, the sample consisted of 105 adolescent inpatients (ages 13–18 years) who received a discharge diagnosis of a mood disorder (excluding bipolar disorder): major depressive disorder (n = 22; 21%), dysthymic disorder/depressive disorder NOS (n = 28; 27%), or mood disorder NOS (n = 55; 53%). In addition to a diagnosed mood disorder in all participants, there was a high prevalence of psychiatric comorbidity in this sample. Demographics and comorbidity were examined either using chi-squared analyses or analyses of variance. Results are provided in Table 1.
TABLE 1 Clinical and Demographic Characteristics for CDI Groups
Variable % Male Age Comorbidity Anxiety Behavioral ADHD
CDI < 60
CDI ≥ 60
Total Sample (N = 105)
Mood Without Depressive Sx (n = 61)
Mood With Depressive Sx (n = 41)
Pearson χ2
57% 15.33 (1.3)
69% 15.33 (1.29)
39% 15.32 (1.34)
8.89**
33% 31% 49%
27% 37% 39%
0.411 0.326 1.021
30% 33% 45%
F .003
Comorbidity = comorbid psychiatric diagnoses at hospital discharge; Anxiety = anxiety disorders; Behavioral = behavioral disorders; ADHD = attention-deficit hyperactivity disorder. **p < .01.
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Materials T-scores were used for depressive and executive-functioning measures.
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Measures of Self-Reported Depression The Children’s Depression Inventory (CDI) is a 27-item self-report measure of depressive symptoms in children and adolescents ages 7 to 17 years old (Kovacs, 1992). The CDI assesses negative mood, interpersonal problems, ineffectiveness, anhedonia, and negative self-esteem. The Minnesota Multiphasic Personality InventoryAdolescent (MMPI-A) is a self-report measure of personality and psychological disorders in the adolescent population (Archer, 1992). There are 10 clinical scales within the MMPI-A, each assessing a different component of mental health. Scale 2 (Depression) measures depressive symptoms experienced by the adolescent, including lack of interest in activities, physical symptoms, and social difficulties (Archer). Scale 2 was the only portion of the MMPI-A that was used for the present study. All completed MMPI-A results were used in this study. This decision to not use exclusion criteria was based on research indicating that validity scales in MMPI instruments can represent genuine distress (Greene, 2000), especially in the adolescent psychiatric inpatient population (Archer). In the clinical assessment protocol at the hospital, both the CDI and MMPI-A are administered to patients. Because of this, both the CDI and the Scale 2 (Depression scale) of the MMPI-A were included in the present study. However, due to the small sample of MMPI-A profiles, only the CDI Total score was used as a grouping variable. Alternatively, MMPI-A Scale 2 and all the CDI scores were included in a correlation analysis. Tasks of Executive Functioning The present study used neuropsychological assessment tools to assess five executive-functioning subdomains: (1) planning/problem solving; (2) set shifting/cognitive flexibility; (3) response inhibition/interference control; (4) fluency; and (5) working memory/simple attention. Planning/Problem Solving. The Wisconsin Card-Sorting Test (WCST) is a test of executive function that assesses skills in abstraction, shifting and maintaining focus, goal orientation, and impulse control (Baron, 2004; Henry & Bettenay, 2010; Strauss, Sherman, & Strauss, 2006; Willcutt, 2010). This study used the following WCST scores: amount of categories achieved (WCST Categories), failures to maintain set (WCST FMS), and perseverative errors (WCST Perseverative Errors). The WCST Categories score was used as a measure of
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planning/problem solving (Baron, 2004; Strauss et al.). The Rey-Osterreith Complex Figure (ROCF) is a neuropsychological task designed to assess visual-spatial, perceptual, planning, integration, and organizational abilities (Strauss et al.). The ROCF requires the participant to copy a picture of a complex geometric design as accurately as possible. The ROCF was used in the present study to assess planning. Set Shifting/Cognitive Flexibility. The Trail-Making Test (TMT) is a neuropsychological instrument that assesses attention, speed, and cognitive flexibility (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006). It consists of two versions that are administered consecutively to the client. TMT-A requires the client to use a pencil and connect encircled numbers in numerical order. TMT-B requires the client to use a pencil and connect encircled numbers and letters in numerical and alphabetical order, alternating between numbers and letters until completed. The adult form is for ages 15 to 89 years old, and the child form is for ages 9 to 14 years old. The child form is very similar to the adult form, although it contains fewer numbers and letters. TMT-B was used in the present study to assess set shifting/cognitive flexibility (Strauss et al.). In addition, the WCST Perseverative Errors score was used to assess set shifting/cognitive flexibility (Baron, 2004). Response Inhibition/Interference Control. The Stroop Test is a verbal task of executive function that assesses processing speed, attention, cognitive flexibility, resistance to distraction, and response inhibition (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006; Willcutt, 2010). It consists of three conditions that require the client to read increasingly difficult patterns of words and colors. The third condition, called Color–Word (C–W), presents a word list of colors, with each color name printed in the ink of another color. For example, the word “RED” would be printed in blue ink, with the participant required to say the color of the ink, not the written word. The increasingly difficult conditions challenge the executive functions of the client. The Stroop C–W score was the only Stroop score used for this study and it was used to assess response inhibition/interference control. In addition, the WCST FMS score was used to assess response inhibition/interference control (Strauss et al.). Fluency. The Controlled Oral Word Association Test (COWAT) is a verbal task that requires the individual to produce words based on clinician-delivered characteristics and is typically viewed as a task assessing executive functioning, specifically verbal fluency (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006). Two conditions were used in this administration—phonemic
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and semantic. The phonemic condition, FAS, asks the client to produce words starting with the letters F, A, and S for 1 minute per letter. The semantic condition, Animals, asks the client to say the names of various animals for one minute. COWAT FAS and Animals were both used to assess fluency, specifically verbal fluency. Working Memory/Simple Attention. The Wide Range Assessment of Memory and Learning (WRAML) is a set of tasks that assesses the learning and memory abilities of children and adolescents (Sheslow & Adams, 1990). One subtest, Sentence Repetition, involves the clinician verbally presenting increasingly difficult sentences to the client, asking the client to repeat the sentence. This subtest, similar to other verbally presented digit span and sentence repetition tasks, is believed to assess working memory and simple attention/concentration (Burton, Donders, & Mittenberg, 1996). Therefore, Sentence Repetition was used in this study to assess working memory. TMT-A was also used in the present study to assess simple attention (Baron, 2004; Strauss et al., 2006).
RESULTS Executive Functions Composite scores were calculated for each executivefunctioning subdomain based on the mean performance of administered executive-functioning measures: cognitive flexibility/set shifting (TMT-B and WCST Perseverative Errors), interference control/response inhibition (Stroop C-W and WCST FMS), planning/problem solving (ROCF and WCST Categories), working memory/ simple attention (WRAML Sentences and TMT-A), and verbal fluency (COWAT FAS and COWAT Animals). In addition, an Executive-Functioning Composite was calculated based on all executive-functioning measures.
CDI and Executive Functioning The CDI Total mean T-score for the sample was 58.8 (14.69). Based on the mean CDI Total T-score as well as interpretive information on the CDI (Kovacs, 1992) and general adolescent self-reporting (Fontaine, Archer, Elkins, & Johansen, 2001), the sample was dichotomized at a CDI Total T-score of 60. A With Depressive Symptoms group (T-score ≥ 60) and a Without Depressive Symptoms group (T-score < 60) were created based on the CDI Total T-score. Clinical and demographic data on the two groups are provided in Table 1. Hierarchical Regression Analyses Hierarchical regression analyses were conducted to determine if CDI grouping contributed significant variance to the executive-functioning subdomains. To ensure that CDI grouping contributed uniquely to the models, the variables sex and attention-deficit hyperactivity disorder (ADHD) diagnosis were entered into the first model and were also the first variables entered into the second model, which also contained CDI grouping. The decision to control for sex and ADHD diagnosis was determined based on chi-squared analyses that determined significant differences between CDI groups on sex (χ 2 = 8.89) and differences between CDI groups that approached significance regarding the presence of ADHD diagnoses (χ 2 = 1.021). The CDI grouping contributed no significant variance to any of the identified executive-functioning subdomain composite scores. In addition, no control variables significantly contributed to any observed variance. Results are provided in Table 2. Correlation Analysis Pearson and Point biserial correlations between demographic variables and executive-functioning and
TABLE 2 Hierarchical Regression Analyses on CDI Grouping and Executive-Functioning Measures Dependent Variable (Domain Composites) Executive Functioning Composite Cognitive Flexibility/ Set Shifting Working Memory/ Simple Attention Response Inhibition/ Interference Control Problem Solving/ Planning Fluency Note. None significant at p < .05.
Model and Independent Variables 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group
R2
Model (F)
.003 .004 .007 .011 .017 .024 .002 .002 .004 .005 .006 .007
.151 .128 .342 .375 .438 .809 .082 .055 .206 .148 .282 .206
R2 Change .001 .005 .008 .000 .000 .001
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TABLE 3 Correlations Between Psychological and Executive Measures
Sex Age ROCF TMT-A TMT-B Stroop C–W WCST Psv WCST Cat WCST FMS FAS Animals Sentences
Sex
Age
CDI Total
CDI Mood
CDI Inter.
CDI Ineff.
CDI Anhed.
CDI S-E
MMPI Sc2
1 .023 –.082 –.170 –.033 –.134 –.273** –.009 –.092 .109 –.02 .047
.023 1 –.298** –.128 –.129 .425** –.105 –.177 –.015 –.171 –.071 .121
–.326** –.056 .184 .053 .027 –.125 .053 –.174 .033 .014 –.003 .006
–.278** –.018 .143 .111 .047 –.158 .062 –.236* .030 –.019 .043 .114
–.096 –.141 .241* –.045 –.096 –.294* –.079 –.250* .070 .065 –.041 –.028
–.211** –.039 .202 .105 .146 –.078 .095 –.004 .094 .122 .08 –.037
–.212* –.052 .112 .004 –.015 –.145 .038 –.116 .114 .013 .055 .069
–.396** –.108 .243* .046 .075 –.110 .037 –.103 –.109 –.058 –.022 –.098
–.239 .010 .181 .203 .055 .264 .177 –.116 .052 .128 .113 .193
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CDI Mood = CDI Negative Mood; CDI Inter. = CDI Interpersonal Problems; CDI Ineff. = CDI Ineffectiveness; CDI Anhed. = CDI Anhedonia; CDI S-E = CDI Negative Self-Esteem; MMPI Sc2 = MMPI-A Scale 2. *p < .05. **p < .01.
depressive symptom measures were examined in Table 3. The CDI Total score did not correlate with any executivefunctioning measures. Although the ExecutiveFunctioning Composite score and CDI Total score did not correlate, their respective subdomains showed evidence of correlation. For example, the CDI Interpersonal Problems subdomain was negatively correlated with performance on Stroop C–W and WCST Categories. In addition, CDI Mood was negatively correlated with WCST Categories. Alternatively, ROCF was positively correlated with CDI Interpersonal Problems and CDI Self-Esteem. In addition, CDI was negatively correlated with sex (1 = female; 2 = male), such that females reported higher depressive symptoms on the majority of CDI subdomains. Sex was also negatively correlated with WCST Perseverative Errors. Age was positively correlated with Stroop C-W but negatively correlated with ROCF.
DISCUSSION This study attempted to examine executive functioning within adolescent depression by using an adolescent inpatient sample diagnosed with a mood disorder. This is the first study to our knowledge that has looked at executive functioning and self-reported depressive symptoms exclusively in an adolescent inpatient sample. When the sample was dichotomized based on selfreported depressive symptoms (CDI Total), CDI grouping did not significantly account for the variance in any executive-functioning subdomains (e.g., planning/problem solving, interference control/response inhibition, set shifting/cognitive flexibility, working memory/simple attention, and fluency). These findings are consistent with the findings from Klimkeit et al. (2011), who found no differences in a defined executive-functioning domain between an adolescent major depression group and an
adolescent minor depression group. However, the results are inconsistent with the findings from Maalouf et al. (2011), who found executive-functioning differences between adolescents with a depression diagnosis and high self-reported depressive symptoms and adolescents with a depression diagnosis but low self-reported depressive symptoms. To summarize the present study, there were no executive-functioning differences between mood disorders with depressive symptoms and mood disorders without depressive symptoms. In addition, the present study also examined the correlations between CDI scores and executive-functioning measures. The CDI Total and the Executive-Functioning Composite were not significantly correlated. However, there were statistically significant (p < .05) correlations between CDI subdomains and select scores on the WCST and the Stroop Test. Specifically, WCST Categories was negatively correlated with the CDI subdomains Negative Mood and Interpersonal Problems. In addition, CDI Interpersonal Problems was also negatively correlated with the Stroop C–W score. Alternatively, ROCF was positively correlated with CDI Interpersonal Problems and CDI Self-Esteem. When using standards set forth by Cohen (1992), with large correlations set at .5, moderate correlations at .3, and small correlations at .1, the current findings could be classified as approaching a moderate level of correlation. Specifically, negative and statistically significant correlations (p < .05) ranged from r = –.236 to –.294, while positive and statistically significant correlations (p < .05) ranged from r = .241 to .243. These correlations are considered small-to-medium levels of correlation, although they are also statistically significant and highlight the clinical utility and clinical significance of identifying such a relationship between executive and depressive subdomains. Notably, this provides important information regarding the potential underlying causes and implicated domains of depression as well as
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information that can be applied clinically to potentially provide executive training supplemental to adolescent depression treatment. While the Executive-Functioning Composite score may be minimally affected by depressive symptoms, researchers have also emphasized the importance of examining the executive-functioning subdomains, not solely the umbrella term “executive functioning” (Baron, 2010). Consistent with this approach, the current study identified certain executive subdomains, such as planning/problem solving and interference control/response inhibition, which may be associated with select depressive symptoms. However, the inconsistent nature of these findings suggests that they should be interpreted with caution. This finding lends partial support to our original hypothesis regarding the association between select executive and depressive subdomains but also causes confusion with regard to the ROCF findings. Research has suggested that using subdomains of a given cognitive domain (e.g., fluency within executive functioning) is not comprehensive enough and that using a more detailed level of evaluation, such as microdomains, may be more appropriate (Baron, 2010). Microdomains have been predominantly explored within working memory (Repovs & Baddeley, 2006); however, the present findings suggest that planning/problem solving (ROCF and WCST Categories) may also be appropriately broken into microdomains, specifically into planning and problem solving. When doing so, present findings indicated a negative correlation between problem-solving abilities and select depressive symptoms, while planning abilities were positively correlated with increased depressive symptoms. The planning abilities finding provides an unclear clinical picture and potentially suggests that certain elevated depressive symptoms are associated with stronger ROCF performance. This could potentially reflect intact visual-motor and planning abilities, suggesting that these abilities may be less resistant to the negative effects of depressive symptoms, while other areas of executive function are more sensitive to depressive symptoms. This further highlights the heterogeneous nature of executive functioning and the need to continuously explore executive subdomains. Generally, the ROCF findings are surprising and warrant further exploration within future executivefunctioning and depression research. In addition to these findings, there were also correlations between demographic variables and measures. Specifically, sex was negatively correlated with self-reported depressive symptoms and also negatively correlated with WCST Categories. Age was negatively correlated with ROCF but positively correlated with Stroop C–W, suggesting that although increases in age were associated with decreased performance on some measures, age increases were associated with increased performance on another
measure. Although it appears that within our sample, females reported greater depressive symptoms and stronger problem-solving abilities, the examination of age and sex on executive functioning needs further examination in future studies to clarify these findings. Also of importance is the overall presence of depressive symptoms within this inpatient sample of adolescents with mood disorders. The sample had mean T-score of 58.8 for the CDI Total. This finding is consistent with prior research that examined CDI responses in 521 child and adolescent inpatients (Liss, Phares, & Liljequist, 2001) and found the average T-score for the sample to be between 57 and 62. The self-reported depressive symptoms similarity to past psychiatric inpatient research within the present study suggests the potential generalizability of our findings. With these findings in mind, there are several limitations to this study. The first limitation was the use of selfreported depressive symptom measures as the primary tool for documenting the level of depression. Particularly on an acute, inpatient setting, adolescents may have difficulty accurately perceiving and/or reporting depressive symptoms. In addition, adolescents may have a motivation to underreport their symptoms or to report symptoms in a biased manner. Previous studies have observed negative effects of a restricted environment on the accuracy of child and adolescent self-reporting, such as in a forensic or psychiatric inpatient setting (Baum, Archer, Forbey, & Handel, 2009; Epkins, 1995). In other words, there is motivation to “fake good” on these measures to improve the chances for accelerated discharge from the hospital (e.g., “flight to health”). For example, although a group of research has used self-report measures of depression within the child and/or adolescent population (Cataldo et al., 2005; Hill et al., in press; Maalouf et al., 2011), the only study that did not find differences or correlations between depressive symptoms and executive functioning was partially done with an inpatient sample (Hill et al.). Although we found select correlations with self-report measures, using self-reported depressive symptoms on an inpatient sample may have limited our findings. A further limitation to our study was the lack of a control group to compare the performance of adolescent inpatients with mood disorders on executive-functioning tasks with the performance of healthy adolescents. The current study was based solely on data gathered from an acutely distressed sample. The sample of participants performed below normative expectations for the general population, regardless of depression classification and across all executive-functioning tasks. Although the purpose of this study was to examine differences within mood disorders to clarify inconsistent prior research, and not to compare our sample to those without mood disorders, we understand the usefulness in using a control
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group. Providing a control group for comparison purposes could have provided information regarding the abilities of adolescents with mood disorders in relation to healthy adolescents. Future studies should continue to examine the relationship between executive functioning and depression within the adolescent inpatient setting, but with an adjusted approach to grouping requirements. This may include relying on primary psychiatric diagnoses assigned by attending psychiatrists as opposed to self-report measures. This at the very least should provide a more accurate baseline from which to explore executive functioning in adolescent depression. The use of historical markers for each individual to distinguish between levels of distress or dysfunction immediately prior to hospitalization may be more useful in terms of developing meaningful groupings (e.g., suicidal ideation vs. no suicidal ideation, suicide attempt vs. no suicide attempt, any self-injury vs. no self-injury, aggression vs. no aggression, etc.). In addition, researchers should continue to examine executivefunctioning subdomains as opposed to solely examining the executive-functioning domain. Researchers should also continue to progress to executive-functioning evaluation at the microdomain level to most accurately examine various functions. Finally, it will be informative to compare the executive functioning of an inpatient population with broad normative data to gain a better understanding of this understudied population. In summary, there were no differences in executivefunctioning subdomains (e.g., planning/problem solving, cognitive flexibility/set shifting, interference control/ response inhibition, working memory/simple attention, and fluency) between those adolescents with mood disorders and depressive symptoms and those adolescents with mood disorders without depressive symptoms. Alternatively, negative correlations were observed between select executive-functioning subdomains (e.g., problem solving and response inhibition/interference control) and certain depressive symptoms (e.g., negative mood and interpersonal problems). This suggests that although overall executive function may not be affected in depressive symptom presentation, certain executive subdomains may be involved in depressive symptoms and thus may require special attention during treatment and treatment planning. Future research should continue to explore the relationship between depressive symptoms and executive functions within the adolescent population to help clarify inconsistent findings. ACKNOWLEDGEMENTS We would like to thank George Tremblay at Antioch University New England for his statistical guidance and the entire neuropsychology team at Butler Hospital.
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Klimkeit, E. I., Tonge, B., Bradshaw, J. L., Melvin, G. A., & Gould, K. (2011). Neuropsychological deficits in adolescent unipolar depression. Archives of Clinical Neuropsychology, 26, 662–676. Koenigs, M., & Grafman, J. (2009). The functional neuroanatomy of depression: Distinct roles for ventromedial and dorsolateral prefrontal cortex. Behavioural Brain Research, 201, 239–243. Kovacs, M. (1992). Children’s Depression Inventory (CDI) manual. New York, NY: Multi-Health Systems. Kyte, Z. A., Goodyer, I. M., & Sahakian, B. J. (2005). Selected executive skills in adolescents with recent first episode major depression. Journal of Child Psychology and Psychiatry, 46, 995–1005. Lezak, M. D., Howieson, D. B., & Loring, D. W. (2004). Neuropsychological assessment (4th ed.). New York, NY: Oxford University Press. Liss, H., Phares, V., & Liljequist, L. (2001). Symptom endorsement differences on the Children’s Depression Inventory with children and adolescents on an inpatient unit. Journal of Personality Assessment, 76, 396–411. Maalouf, F. T., Brent, D., Clark, L., Tavitian, L., McHugh, R. M., Sahakian, B. J., & Phillips, M. L. (2011). Neurocognitive impairment in adolescent major depressive disorder: State vs. trait illness markers. Journal of Affective Disorders, 133, 625–632. Mahone, E. M., & Slomine, B. S. (2007). Managing dysexecutive disorders. In S. J. Hunter & J. Donders (Eds.), Pediatric neuropsychological intervention (pp. 287–313). New York, NY: Cambridge University Press. Mash, E. J., & Barkley, R. A. (Eds.). (2007). Assessment of childhood disorders (4th ed.). New York, NY: Guilford Press. Matthews, K., Coghill, D., & Rhodes, S. (2008). Neuropsychological functioning in depressed adolescent girls. Journal of Affective Disorders, 111, 113–118. McClure, E., Rogeness, G. A., & Thompson, N. M. (1997). Characteristics of adolescent girls with depressive symptoms in a so-called ‘normal’ sample. Journal of Affective Disorders, 42, 187–197.
McDermott, L. M., & Ebmeier, K. P. (2009). A meta-analysis of depression severity and cognitive function. Journal of Affective Disorders, 119, 1–8. Murray, E. A., Wise, S. P., & Drevets, W. C. (2011). Localization of dysfunction in major depressive disorder: Prefrontal cortex and amygdala. Biological Psychiatry, 69, 43–54. National Institute of Mental Health. (2001). Mood disorders in children and adolescents: An NIMH perspective. Biological Psychiatry, 49, 962–969. Ottowitz, W. E., Dougherty, D. D., & Savage, C. R. (2002). The neural network basis for abnormalities of attention and executive function in major depressive disorder: Implications for application of the medical disease model to psychiatric disorders. Harvard Review of Psychiatry, 10, 86–99. Porter, R. J., Bourke, C., & Gallagher, P. (2007). Neuropsychological impairment in major depression: Its nature, origin, and clinical significance. Australian and New Zealand Journal of Psychiatry, 41, 115–128. Price, J. L., & Drevets, W. C. (2012). Neural circuits underlying the pathophysiology of mood disorders. Trends in Cognitive Sciences, 16, 61–71. Repovs, G., & Baddeley, A. (2006). The multi-component model of working memory: Explorations in experimental cognitive psychology. Neuroscience, 139, 5–21. Sheslow, D., & Adams, W. (1990). WRAML: Wide Range Assessment of Memory and Learning administration manual. Wilmington, DE: Jastak Assessment Systems. Strauss, E., Sherman, E. M., & Strauss, O. (2006). A compendium of neuropsychological tests: Administration, norms and commentary (3rd ed.). New York, NY: Oxford University Press. Willcutt, E. G. (2010). Attention-deficit/hyperactivity disorder. In K. O. Yeates, M. D. Ris, H. G. Taylor, & B. F. Pennington (Eds.), Pediatric neuropsychology: Research, theory, and practice (2nd ed., pp. 393–417). New York, NY: The Guilford Press.
Applied Neuropsychology: Child Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/hapc20
Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population a
Brian Kavanaugh & Karen Holler
b
a
Department of Clinical Psychology , Antioch University New England , Keene , New Hampshire b
Department of Psychiatry and Human Behavior , Alpert Medical School of Brown University , Providence , Rhode Island Published online: 20 Nov 2012.
Click for updates To cite this article: Brian Kavanaugh & Karen Holler (2014) Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population, Applied Neuropsychology: Child, 3:2, 126-134, DOI: 10.1080/21622965.2012.731662 To link to this article: http://dx.doi.org/10.1080/21622965.2012.731662
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APPLIED NEUROPSYCHOLOGY: CHILD, 3: 126–134, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 2162-2965 print/2162-2973 online DOI: 10.1080/21622965.2012.731662
Executive Functioning and Self-Reported Depressive Symptoms Within an Adolescent Inpatient Population Brian Kavanaugh Department of Clinical Psychology, Antioch University New England, Keene, New Hampshire
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Karen Holler Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island
Although the relationship between executive dysfunction and depressive disorders has been well established in the adult population, research within the adolescent population has produced mixed results. The present study examined executive-functioning subdomains in varying levels of self-reported depression within an adolescent inpatient sample diagnosed with primary mood disorders. Via retrospective chart review, the sample consisted of those adolescents (ages 13–18 years) who completed a combined psychological/neuropsychological assessment during hospitalization (N = 105). When the sample was divided into adolescents with mood disorders with self-reported depressive symptoms and adolescents with mood disorders without self-reported depressive symptoms, no differences in various executive functions were identified. There were also no correlations between overall self-reported depressive symptoms and overall executive functioning. However, there were negative correlations between select executive subdomains (e.g., problem solving and response inhibition) and certain depressive symptom subdomains (e.g., negative mood and interpersonal problems). Based on these findings, there was no difference in executive functions between mood disorders with depressive symptoms and mood disorders without depressive symptoms, although there may be select executive subdomains that are particularly involved in certain depressive symptoms, providing important information for the treatment of adolescent depression.
Key words:
adolescents, depression, executive functioning, inpatient, mood disorder
Recent research has identified neural correlates of depression, notably in the medial prefrontal cortex (Koenigs & Grafman, 2009; Murray, Wise, & Drevets, 2011; Price & Drevets, 2012), dorsolateral prefrontal cortex (DLPFC; Koenigs & Grafman; Ottowitz, Dougherty, & Savage, 2002), striatum (Ottowitz et al.; Price & Drevets), thalamus (Ottowitz et al.; Price & Drevets), and basal forebrain structures (Price & Drevets). Specific depressive symptoms have been identified within this neural Address correspondence to Brian Kavanaugh, Department of Clinical Psychology, Antioch University New England, 40 Avon Street, Keene, NH 03431. E-mail: [email protected]
network, including anhedonia, negative affect, and negative self-image/self-rumination (Koenigs & Grafman; Price & Drevets). The cognitive domain “executive functioning” consists of a heterogeneous set of cognitive functions responsible for planning, organizing and executing behaviors, problem solving, inhibiting inappropriate behavior and resisting distraction, fluency, working memory, and cognitive flexibility/set shifting, with impaired executive functions resulting in, or contributing to, a range of potential behavioral deficiencies (Anderson, 2002; Baron, 2004; Henry & Bettenay, 2010; Lezak, Howieson, & Loring, 2004; Mahone & Slomine, 2007; Willcutt, 2010).
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The prefrontal cortex (PFC) has typically been identified as the primary neural correlate of executive functioning, specifically in the subdomains of interference control/inhibition, working memory, planning, and set shifting (Collette et al., 2005; Willcutt, 2010). Notable structures associated with executive functioning include the circuit involving the DLPFC/ventrolateral PFC/orbitofrontal cortex (Collette et al.; Koenigs & Grafman, 2009; Ottowitz et al., 2002; Willcutt), thalamus (Ottowitz et al.; Willcutt), striatum (Ottowitz et al.) and basal ganglia (Willcutt). In addition to the association with prefrontal cortical regions, specific executive-functioning subdomains have been associated with differing neural substrates (Collette et al.). For example, selective attention and interference control have involved the right intraparietal sulcus, while set shifting/integration has been associated with the superior parietal region of the brain (Collette et al.). Based on the shared neural correlates between depression and executive functions (e.g., DLPFC, thalamus, striatum, and basal structures), theory has proposed and research has identified a link between adult depression and executive functioning, notably identifying executive dysfunction within adult depression (Castaneda, Tuulio-Henriksson, Marttunen, Suvisaari, & Lonnqvist, 2008; McDermott & Ebmeier, 2009; Ottowitz et al., 2002; Porter, Bourke, & Gallagher, 2007). However, the research on executive dysfunction within child and adolescent depression is still very inconsistent. With increased research in recent years within child and/or adolescent depression, the majority of research has identified at least partial executive dysfunction, specifically in interference control/response inhibition (Brooks, Iverson, Sherman, & Roberge, 2010; Cataldo, Noblie, Lorusso, Battaglia, & Molteni, 2005; Kyte, Goodyer, Sahakian, 2005), initiation/planning of behavior (Cataldo et al.; Maalouf et al., 2011), set shifting (Brooks et al.), working memory (Klimkeit, Tonge, Bradshaw, Melvin, & Gould, 2011; Matthews, Coghill, & Rhodes, 2008), verbal fluency (Klimkeit et al.), and impulsivity (Brooks et al.; Kyte et al.; Maalouf et al.). Alternatively, a portion of the research has found intact executive functioning (Favre et al., 2009; Halari et al., 2009; Hill, Ploetz, O’Jile, Bodzy, & Holler, in press; McClure, Rogeness, & Thompson, 1997). Two of these studies have examined the child/ adolescent depression–executive dysfunction association with self-report measures (Cataldo et al., 2005; Hill et al., in press). Cataldo et al. examined the executive functioning of 21 children and adolescents diagnosed with a mood disorder and 21 children and adolescents serving as a control group. Within those participants diagnosed with a mood disorder, there was a negative correlation between self-reported depressive symptoms and interference control/ response inhibition. Alternatively, Hill et al. examined the
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association between self-reported depressive symptoms and executive functioning in a mixed sample of 170 children and adolescents within an inpatient and outpatient setting. Results of this study indicated no significant association between self-reported depressive symptoms and any measured executive-functioning subdomains. Although findings within child and/or adolescent samples are important to consider, child and adolescent depression can have very significant differences, making it important to study these conditions as separate entities (Crowe, Ward, Dunnachie, & Roberts, 2006; Mash & Barkley, 2007; National Institute of Mental Health, 2001). Relatedly, some of the neuropsychological research has looked solely at adolescent depression and executive functioning (Halari et al., 2009; Klimkeit et al., 2011; Kyte et al., 2005; Maalouf et al., 2011; Matthews et al., 2008; McClure et al., 1997), with four studies finding at least partial evidence of dysfunction in select executive-functioning subdomains within adolescent depression (Klimkeit et al.; Kyte et al.; Maalouf et al.; Matthews et al.). Notably, two studies have examined the severity of adolescent depression in relation to executive functioning (Klimkeit et al., 2011; Maalouf et al., 2011). Maalouf et al. examined 40 adolescents diagnosed with major depressive disorder and dichotomized the sample into an active depression group and a remitted depression group based on a measure of self-reported depressive symptoms. Active depression was associated with impaired planning/problem solving and impulsivity when compared with the remitted depression group as well as a control group. These results indicated that when dichotomized, self-reported depressive symptoms might be associated with certain executive functions within adolescent depression. Klimkeit et al. examined the neuropsychological functioning of major and minor depression within a sample of 34 depressed adolescents and 33 adolescent controls. Although the authors noted executive dysfunction was not identified in either depressive group, both depression groups were characterized by impaired performance on tasks of working memory and verbal fluency. The present study attempted to contribute to the growing body of research on adolescent depression and executive functioning, specifically regarding the inconsistent findings regarding the association between self-reported depressive symptoms and executive functioning (Cataldo et al., 2005; Hill et al., in press; Maalouf et al., 2011). To do so, this study examined the association between selfreported depressive symptoms and executive functioning within an adolescent inpatient sample diagnosed with a mood disorder. Consistent with previous research, this study used a diagnosis of a mood disorder as inclusion criteria but used self-reported depressive symptoms to identify the association between executive functioning and depression (Cataldo et al.; Maalouf et al.).
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It was deemed that the term “executive functioning” was too heterogeneous in nature and therefore should not be defined as a unitary construct (Anderson, 2002; Baron, 2004, 2010; Henry & Bettenay, 2010; Willcutt, 2010). After reviewing the child and adolescent neuropsychological literature on executive functioning (Anderson; Baron, 2004, 2010; Henry & Bettenay; Willcutt), five subdomains of executive functioning were identified for the present study: (1) planning/problem solving; (2) set shifting/cognitive flexibility; (3) response inhibition/interference control; (4) fluency; and (5) working memory/simple attention. It was hypothesized that adolescent mood disorders with depressive symptoms would be associated with lower performance in a range of executive-functioning domains (e.g., planning/problem solving, inhibition/interference control, set shifting/cognitive flexibility, verbal fluency, and working memory/simple attention) compared with adolescent mood disorders without depressive symptoms. Based on the literature identifying shared neural correlates between depression and executive functioning, it was hypothesized that select depressive symptoms (e.g., negative affect, anhedonia, and negative self-image) would be negatively correlated with certain executive functions (e.g., inhibition/interference control, planning/problem solving, working memory/simple attention, and set shifting/cognitive flexibility), such that the increased presence of these depressive symptoms would be associated with decreased performance in these executive-functioning subdomains.
METHODS Participants and Procedure This study followed the ethical principles of the American Psychological Association. In addition, this study received institutional review board approval from Butler Hospital. This study is part of a research project examining neuropsychological correlates of psychiatric conditions in
adolescents at Butler Hospital, an inpatient psychiatric hospital. The data were gathered by retrospective chart review for inpatient adolescents who participated in a combined psychological/neuropsychological assessment during 2002 to 2012. Assessments were conducted by a clinical child neuropsychologist, a professional psychometrist, or a doctoral student in clinical psychology under the direct supervision of a child neuropsychologist. All hospitalized adolescents received an admitting diagnosis and a discharge diagnosis by their attending psychiatrist (or medical resident under supervision of an attending psychiatrist), based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental DisordersFourth Edition, Text Revision (American Psychiatric Association, 2000). However, not all adolescents participate in a psychological/neuropsychological assessment. Referrals for evaluation are based on the parent/guardian concerns or a request for additional information by the attending psychiatrist. Assessments are typically completed within a few days of the hospital admission. The present study focused on the relationship between self-reported depressive symptoms and performance on measures of executive functioning in mood disorders within the adolescent inpatient setting. Inpatients with a diagnosis of bipolar disorder, a pervasive developmental disorder (e.g., autistic disorder, Asperger’s disorder, Rett’s disorder, childhood disintegrative disorder, and pervasive developmental disorder-not otherwise specified [NOS]), or a psychotic disorder were not included in the study. Therefore, the sample consisted of 105 adolescent inpatients (ages 13–18 years) who received a discharge diagnosis of a mood disorder (excluding bipolar disorder): major depressive disorder (n = 22; 21%), dysthymic disorder/depressive disorder NOS (n = 28; 27%), or mood disorder NOS (n = 55; 53%). In addition to a diagnosed mood disorder in all participants, there was a high prevalence of psychiatric comorbidity in this sample. Demographics and comorbidity were examined either using chi-squared analyses or analyses of variance. Results are provided in Table 1.
TABLE 1 Clinical and Demographic Characteristics for CDI Groups
Variable % Male Age Comorbidity Anxiety Behavioral ADHD
CDI < 60
CDI ≥ 60
Total Sample (N = 105)
Mood Without Depressive Sx (n = 61)
Mood With Depressive Sx (n = 41)
Pearson χ2
57% 15.33 (1.3)
69% 15.33 (1.29)
39% 15.32 (1.34)
8.89**
33% 31% 49%
27% 37% 39%
0.411 0.326 1.021
30% 33% 45%
F .003
Comorbidity = comorbid psychiatric diagnoses at hospital discharge; Anxiety = anxiety disorders; Behavioral = behavioral disorders; ADHD = attention-deficit hyperactivity disorder. **p < .01.
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Materials T-scores were used for depressive and executive-functioning measures.
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Measures of Self-Reported Depression The Children’s Depression Inventory (CDI) is a 27-item self-report measure of depressive symptoms in children and adolescents ages 7 to 17 years old (Kovacs, 1992). The CDI assesses negative mood, interpersonal problems, ineffectiveness, anhedonia, and negative self-esteem. The Minnesota Multiphasic Personality InventoryAdolescent (MMPI-A) is a self-report measure of personality and psychological disorders in the adolescent population (Archer, 1992). There are 10 clinical scales within the MMPI-A, each assessing a different component of mental health. Scale 2 (Depression) measures depressive symptoms experienced by the adolescent, including lack of interest in activities, physical symptoms, and social difficulties (Archer). Scale 2 was the only portion of the MMPI-A that was used for the present study. All completed MMPI-A results were used in this study. This decision to not use exclusion criteria was based on research indicating that validity scales in MMPI instruments can represent genuine distress (Greene, 2000), especially in the adolescent psychiatric inpatient population (Archer). In the clinical assessment protocol at the hospital, both the CDI and MMPI-A are administered to patients. Because of this, both the CDI and the Scale 2 (Depression scale) of the MMPI-A were included in the present study. However, due to the small sample of MMPI-A profiles, only the CDI Total score was used as a grouping variable. Alternatively, MMPI-A Scale 2 and all the CDI scores were included in a correlation analysis. Tasks of Executive Functioning The present study used neuropsychological assessment tools to assess five executive-functioning subdomains: (1) planning/problem solving; (2) set shifting/cognitive flexibility; (3) response inhibition/interference control; (4) fluency; and (5) working memory/simple attention. Planning/Problem Solving. The Wisconsin Card-Sorting Test (WCST) is a test of executive function that assesses skills in abstraction, shifting and maintaining focus, goal orientation, and impulse control (Baron, 2004; Henry & Bettenay, 2010; Strauss, Sherman, & Strauss, 2006; Willcutt, 2010). This study used the following WCST scores: amount of categories achieved (WCST Categories), failures to maintain set (WCST FMS), and perseverative errors (WCST Perseverative Errors). The WCST Categories score was used as a measure of
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planning/problem solving (Baron, 2004; Strauss et al.). The Rey-Osterreith Complex Figure (ROCF) is a neuropsychological task designed to assess visual-spatial, perceptual, planning, integration, and organizational abilities (Strauss et al.). The ROCF requires the participant to copy a picture of a complex geometric design as accurately as possible. The ROCF was used in the present study to assess planning. Set Shifting/Cognitive Flexibility. The Trail-Making Test (TMT) is a neuropsychological instrument that assesses attention, speed, and cognitive flexibility (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006). It consists of two versions that are administered consecutively to the client. TMT-A requires the client to use a pencil and connect encircled numbers in numerical order. TMT-B requires the client to use a pencil and connect encircled numbers and letters in numerical and alphabetical order, alternating between numbers and letters until completed. The adult form is for ages 15 to 89 years old, and the child form is for ages 9 to 14 years old. The child form is very similar to the adult form, although it contains fewer numbers and letters. TMT-B was used in the present study to assess set shifting/cognitive flexibility (Strauss et al.). In addition, the WCST Perseverative Errors score was used to assess set shifting/cognitive flexibility (Baron, 2004). Response Inhibition/Interference Control. The Stroop Test is a verbal task of executive function that assesses processing speed, attention, cognitive flexibility, resistance to distraction, and response inhibition (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006; Willcutt, 2010). It consists of three conditions that require the client to read increasingly difficult patterns of words and colors. The third condition, called Color–Word (C–W), presents a word list of colors, with each color name printed in the ink of another color. For example, the word “RED” would be printed in blue ink, with the participant required to say the color of the ink, not the written word. The increasingly difficult conditions challenge the executive functions of the client. The Stroop C–W score was the only Stroop score used for this study and it was used to assess response inhibition/interference control. In addition, the WCST FMS score was used to assess response inhibition/interference control (Strauss et al.). Fluency. The Controlled Oral Word Association Test (COWAT) is a verbal task that requires the individual to produce words based on clinician-delivered characteristics and is typically viewed as a task assessing executive functioning, specifically verbal fluency (Baron, 2004; Henry & Bettenay, 2010; Strauss et al., 2006). Two conditions were used in this administration—phonemic
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and semantic. The phonemic condition, FAS, asks the client to produce words starting with the letters F, A, and S for 1 minute per letter. The semantic condition, Animals, asks the client to say the names of various animals for one minute. COWAT FAS and Animals were both used to assess fluency, specifically verbal fluency. Working Memory/Simple Attention. The Wide Range Assessment of Memory and Learning (WRAML) is a set of tasks that assesses the learning and memory abilities of children and adolescents (Sheslow & Adams, 1990). One subtest, Sentence Repetition, involves the clinician verbally presenting increasingly difficult sentences to the client, asking the client to repeat the sentence. This subtest, similar to other verbally presented digit span and sentence repetition tasks, is believed to assess working memory and simple attention/concentration (Burton, Donders, & Mittenberg, 1996). Therefore, Sentence Repetition was used in this study to assess working memory. TMT-A was also used in the present study to assess simple attention (Baron, 2004; Strauss et al., 2006).
RESULTS Executive Functions Composite scores were calculated for each executivefunctioning subdomain based on the mean performance of administered executive-functioning measures: cognitive flexibility/set shifting (TMT-B and WCST Perseverative Errors), interference control/response inhibition (Stroop C-W and WCST FMS), planning/problem solving (ROCF and WCST Categories), working memory/ simple attention (WRAML Sentences and TMT-A), and verbal fluency (COWAT FAS and COWAT Animals). In addition, an Executive-Functioning Composite was calculated based on all executive-functioning measures.
CDI and Executive Functioning The CDI Total mean T-score for the sample was 58.8 (14.69). Based on the mean CDI Total T-score as well as interpretive information on the CDI (Kovacs, 1992) and general adolescent self-reporting (Fontaine, Archer, Elkins, & Johansen, 2001), the sample was dichotomized at a CDI Total T-score of 60. A With Depressive Symptoms group (T-score ≥ 60) and a Without Depressive Symptoms group (T-score < 60) were created based on the CDI Total T-score. Clinical and demographic data on the two groups are provided in Table 1. Hierarchical Regression Analyses Hierarchical regression analyses were conducted to determine if CDI grouping contributed significant variance to the executive-functioning subdomains. To ensure that CDI grouping contributed uniquely to the models, the variables sex and attention-deficit hyperactivity disorder (ADHD) diagnosis were entered into the first model and were also the first variables entered into the second model, which also contained CDI grouping. The decision to control for sex and ADHD diagnosis was determined based on chi-squared analyses that determined significant differences between CDI groups on sex (χ 2 = 8.89) and differences between CDI groups that approached significance regarding the presence of ADHD diagnoses (χ 2 = 1.021). The CDI grouping contributed no significant variance to any of the identified executive-functioning subdomain composite scores. In addition, no control variables significantly contributed to any observed variance. Results are provided in Table 2. Correlation Analysis Pearson and Point biserial correlations between demographic variables and executive-functioning and
TABLE 2 Hierarchical Regression Analyses on CDI Grouping and Executive-Functioning Measures Dependent Variable (Domain Composites) Executive Functioning Composite Cognitive Flexibility/ Set Shifting Working Memory/ Simple Attention Response Inhibition/ Interference Control Problem Solving/ Planning Fluency Note. None significant at p < .05.
Model and Independent Variables 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group 1. Gender and ADHD 2. Gender and ADHD and CDI Group
R2
Model (F)
.003 .004 .007 .011 .017 .024 .002 .002 .004 .005 .006 .007
.151 .128 .342 .375 .438 .809 .082 .055 .206 .148 .282 .206
R2 Change .001 .005 .008 .000 .000 .001
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TABLE 3 Correlations Between Psychological and Executive Measures
Sex Age ROCF TMT-A TMT-B Stroop C–W WCST Psv WCST Cat WCST FMS FAS Animals Sentences
Sex
Age
CDI Total
CDI Mood
CDI Inter.
CDI Ineff.
CDI Anhed.
CDI S-E
MMPI Sc2
1 .023 –.082 –.170 –.033 –.134 –.273** –.009 –.092 .109 –.02 .047
.023 1 –.298** –.128 –.129 .425** –.105 –.177 –.015 –.171 –.071 .121
–.326** –.056 .184 .053 .027 –.125 .053 –.174 .033 .014 –.003 .006
–.278** –.018 .143 .111 .047 –.158 .062 –.236* .030 –.019 .043 .114
–.096 –.141 .241* –.045 –.096 –.294* –.079 –.250* .070 .065 –.041 –.028
–.211** –.039 .202 .105 .146 –.078 .095 –.004 .094 .122 .08 –.037
–.212* –.052 .112 .004 –.015 –.145 .038 –.116 .114 .013 .055 .069
–.396** –.108 .243* .046 .075 –.110 .037 –.103 –.109 –.058 –.022 –.098
–.239 .010 .181 .203 .055 .264 .177 –.116 .052 .128 .113 .193
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CDI Mood = CDI Negative Mood; CDI Inter. = CDI Interpersonal Problems; CDI Ineff. = CDI Ineffectiveness; CDI Anhed. = CDI Anhedonia; CDI S-E = CDI Negative Self-Esteem; MMPI Sc2 = MMPI-A Scale 2. *p < .05. **p < .01.
depressive symptom measures were examined in Table 3. The CDI Total score did not correlate with any executivefunctioning measures. Although the ExecutiveFunctioning Composite score and CDI Total score did not correlate, their respective subdomains showed evidence of correlation. For example, the CDI Interpersonal Problems subdomain was negatively correlated with performance on Stroop C–W and WCST Categories. In addition, CDI Mood was negatively correlated with WCST Categories. Alternatively, ROCF was positively correlated with CDI Interpersonal Problems and CDI Self-Esteem. In addition, CDI was negatively correlated with sex (1 = female; 2 = male), such that females reported higher depressive symptoms on the majority of CDI subdomains. Sex was also negatively correlated with WCST Perseverative Errors. Age was positively correlated with Stroop C-W but negatively correlated with ROCF.
DISCUSSION This study attempted to examine executive functioning within adolescent depression by using an adolescent inpatient sample diagnosed with a mood disorder. This is the first study to our knowledge that has looked at executive functioning and self-reported depressive symptoms exclusively in an adolescent inpatient sample. When the sample was dichotomized based on selfreported depressive symptoms (CDI Total), CDI grouping did not significantly account for the variance in any executive-functioning subdomains (e.g., planning/problem solving, interference control/response inhibition, set shifting/cognitive flexibility, working memory/simple attention, and fluency). These findings are consistent with the findings from Klimkeit et al. (2011), who found no differences in a defined executive-functioning domain between an adolescent major depression group and an
adolescent minor depression group. However, the results are inconsistent with the findings from Maalouf et al. (2011), who found executive-functioning differences between adolescents with a depression diagnosis and high self-reported depressive symptoms and adolescents with a depression diagnosis but low self-reported depressive symptoms. To summarize the present study, there were no executive-functioning differences between mood disorders with depressive symptoms and mood disorders without depressive symptoms. In addition, the present study also examined the correlations between CDI scores and executive-functioning measures. The CDI Total and the Executive-Functioning Composite were not significantly correlated. However, there were statistically significant (p < .05) correlations between CDI subdomains and select scores on the WCST and the Stroop Test. Specifically, WCST Categories was negatively correlated with the CDI subdomains Negative Mood and Interpersonal Problems. In addition, CDI Interpersonal Problems was also negatively correlated with the Stroop C–W score. Alternatively, ROCF was positively correlated with CDI Interpersonal Problems and CDI Self-Esteem. When using standards set forth by Cohen (1992), with large correlations set at .5, moderate correlations at .3, and small correlations at .1, the current findings could be classified as approaching a moderate level of correlation. Specifically, negative and statistically significant correlations (p < .05) ranged from r = –.236 to –.294, while positive and statistically significant correlations (p < .05) ranged from r = .241 to .243. These correlations are considered small-to-medium levels of correlation, although they are also statistically significant and highlight the clinical utility and clinical significance of identifying such a relationship between executive and depressive subdomains. Notably, this provides important information regarding the potential underlying causes and implicated domains of depression as well as
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information that can be applied clinically to potentially provide executive training supplemental to adolescent depression treatment. While the Executive-Functioning Composite score may be minimally affected by depressive symptoms, researchers have also emphasized the importance of examining the executive-functioning subdomains, not solely the umbrella term “executive functioning” (Baron, 2010). Consistent with this approach, the current study identified certain executive subdomains, such as planning/problem solving and interference control/response inhibition, which may be associated with select depressive symptoms. However, the inconsistent nature of these findings suggests that they should be interpreted with caution. This finding lends partial support to our original hypothesis regarding the association between select executive and depressive subdomains but also causes confusion with regard to the ROCF findings. Research has suggested that using subdomains of a given cognitive domain (e.g., fluency within executive functioning) is not comprehensive enough and that using a more detailed level of evaluation, such as microdomains, may be more appropriate (Baron, 2010). Microdomains have been predominantly explored within working memory (Repovs & Baddeley, 2006); however, the present findings suggest that planning/problem solving (ROCF and WCST Categories) may also be appropriately broken into microdomains, specifically into planning and problem solving. When doing so, present findings indicated a negative correlation between problem-solving abilities and select depressive symptoms, while planning abilities were positively correlated with increased depressive symptoms. The planning abilities finding provides an unclear clinical picture and potentially suggests that certain elevated depressive symptoms are associated with stronger ROCF performance. This could potentially reflect intact visual-motor and planning abilities, suggesting that these abilities may be less resistant to the negative effects of depressive symptoms, while other areas of executive function are more sensitive to depressive symptoms. This further highlights the heterogeneous nature of executive functioning and the need to continuously explore executive subdomains. Generally, the ROCF findings are surprising and warrant further exploration within future executivefunctioning and depression research. In addition to these findings, there were also correlations between demographic variables and measures. Specifically, sex was negatively correlated with self-reported depressive symptoms and also negatively correlated with WCST Categories. Age was negatively correlated with ROCF but positively correlated with Stroop C–W, suggesting that although increases in age were associated with decreased performance on some measures, age increases were associated with increased performance on another
measure. Although it appears that within our sample, females reported greater depressive symptoms and stronger problem-solving abilities, the examination of age and sex on executive functioning needs further examination in future studies to clarify these findings. Also of importance is the overall presence of depressive symptoms within this inpatient sample of adolescents with mood disorders. The sample had mean T-score of 58.8 for the CDI Total. This finding is consistent with prior research that examined CDI responses in 521 child and adolescent inpatients (Liss, Phares, & Liljequist, 2001) and found the average T-score for the sample to be between 57 and 62. The self-reported depressive symptoms similarity to past psychiatric inpatient research within the present study suggests the potential generalizability of our findings. With these findings in mind, there are several limitations to this study. The first limitation was the use of selfreported depressive symptom measures as the primary tool for documenting the level of depression. Particularly on an acute, inpatient setting, adolescents may have difficulty accurately perceiving and/or reporting depressive symptoms. In addition, adolescents may have a motivation to underreport their symptoms or to report symptoms in a biased manner. Previous studies have observed negative effects of a restricted environment on the accuracy of child and adolescent self-reporting, such as in a forensic or psychiatric inpatient setting (Baum, Archer, Forbey, & Handel, 2009; Epkins, 1995). In other words, there is motivation to “fake good” on these measures to improve the chances for accelerated discharge from the hospital (e.g., “flight to health”). For example, although a group of research has used self-report measures of depression within the child and/or adolescent population (Cataldo et al., 2005; Hill et al., in press; Maalouf et al., 2011), the only study that did not find differences or correlations between depressive symptoms and executive functioning was partially done with an inpatient sample (Hill et al.). Although we found select correlations with self-report measures, using self-reported depressive symptoms on an inpatient sample may have limited our findings. A further limitation to our study was the lack of a control group to compare the performance of adolescent inpatients with mood disorders on executive-functioning tasks with the performance of healthy adolescents. The current study was based solely on data gathered from an acutely distressed sample. The sample of participants performed below normative expectations for the general population, regardless of depression classification and across all executive-functioning tasks. Although the purpose of this study was to examine differences within mood disorders to clarify inconsistent prior research, and not to compare our sample to those without mood disorders, we understand the usefulness in using a control
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group. Providing a control group for comparison purposes could have provided information regarding the abilities of adolescents with mood disorders in relation to healthy adolescents. Future studies should continue to examine the relationship between executive functioning and depression within the adolescent inpatient setting, but with an adjusted approach to grouping requirements. This may include relying on primary psychiatric diagnoses assigned by attending psychiatrists as opposed to self-report measures. This at the very least should provide a more accurate baseline from which to explore executive functioning in adolescent depression. The use of historical markers for each individual to distinguish between levels of distress or dysfunction immediately prior to hospitalization may be more useful in terms of developing meaningful groupings (e.g., suicidal ideation vs. no suicidal ideation, suicide attempt vs. no suicide attempt, any self-injury vs. no self-injury, aggression vs. no aggression, etc.). In addition, researchers should continue to examine executivefunctioning subdomains as opposed to solely examining the executive-functioning domain. Researchers should also continue to progress to executive-functioning evaluation at the microdomain level to most accurately examine various functions. Finally, it will be informative to compare the executive functioning of an inpatient population with broad normative data to gain a better understanding of this understudied population. In summary, there were no differences in executivefunctioning subdomains (e.g., planning/problem solving, cognitive flexibility/set shifting, interference control/ response inhibition, working memory/simple attention, and fluency) between those adolescents with mood disorders and depressive symptoms and those adolescents with mood disorders without depressive symptoms. Alternatively, negative correlations were observed between select executive-functioning subdomains (e.g., problem solving and response inhibition/interference control) and certain depressive symptoms (e.g., negative mood and interpersonal problems). This suggests that although overall executive function may not be affected in depressive symptom presentation, certain executive subdomains may be involved in depressive symptoms and thus may require special attention during treatment and treatment planning. Future research should continue to explore the relationship between depressive symptoms and executive functions within the adolescent population to help clarify inconsistent findings. ACKNOWLEDGEMENTS We would like to thank George Tremblay at Antioch University New England for his statistical guidance and the entire neuropsychology team at Butler Hospital.
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